• DocumentCode
    2918631
  • Title

    A theory of multi-perspective defocusing

  • Author

    Ding, Yuanyuan ; Xiao, Jing ; Yu, Jingyi

  • Author_Institution
    Univ. of Delaware, Newark, DE, USA
  • fYear
    2011
  • fDate
    20-25 June 2011
  • Firstpage
    217
  • Lastpage
    224
  • Abstract
    We present a novel theory for characterizing defocus blurs in multi-perspective cameras such as catadioptric mirrors. Our approach studies how multi-perspective ray geometry transforms under the thin lens. We first use the General Linear Cameras (GLCs) to approximate the incident multi-perspective rays to the lens and then apply a Thin Lens Operator (TLO) to map an incident GLC to the exit GLC. To study defocus blurs caused by the GLC rays, we further introduce a new Ray Spread Function (RSF) model analogous the Point Spread Function (PSF). While PSF models defocus blurs caused by a 3D scene point, RSF models blurs spread by rays. We derive closed form RSFs for incident GLC rays, and we show that for catadioptric cameras with a circular aperture, the RSF can be effectively approximated as a single or mixtures of elliptic-shaped kernels. We apply our method for predicting defocus blurs on commonly used catadioptric cameras and for reducing de-focus blurs in catadioptric projections. Experiments on synthetic and real data demonstrate the accuracy and general applicability of our approach.
  • Keywords
    approximation theory; cameras; computational geometry; image restoration; lenses; solid modelling; 3D scene point; PSF model defocus blur; RSF model; catadioptric camera mirror; circular aperture; elliptic-shaped kernel; general linear camera; incident GLC rays; incident multiperspective ray geometry transform; multiperspective camera; multiperspective defocusing theory; point spread function; ray spread function model analogous; tltin lens operator; Apertures; Cameras; Geometry; Lenses; Mirrors; Three dimensional displays; Transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4577-0394-2
  • Type

    conf

  • DOI
    10.1109/CVPR.2011.5995617
  • Filename
    5995617